The AIRUSE-LIFE+ project aims at characterizing similarities and heterogeneities in particulate matter (PM) sources and contributions in urban areas from southern Europe. Once the main PMx sources are identified, AIRUSE aims at developing and testing the efficiency of specific and non-specific measures to improve urban air quality. This article reports the results of the source apportionment of PM₁₀ and PM_2.5 conducted at three urban background sites (Barcelona, Florence and Milan, BCN-UB, FI-UB and MLN-UB), one suburban background site (Athens, ATH-SUB) and one traffic site (Porto, POR-TR). After collecting 1047 PM₁₀ and 1116 PM_2.5 24 h samples during 12 months (from January 2013 on) simultaneously at the five cities, these were analysed for the contents of OC, EC, anions, cations, major and trace elements and levoglucosan. The USEPA PMF5 receptor model was applied to these data sets in a harmonized way for each city. The sum of vehicle exhaust (VEX) and non-exhaust (NEX) contributes between 3.9 and 10.8 µg m⁻³ (16–32 %) to PM₁₀ and 2.3 and 9.4 µg m⁻³ (15–36 %) to PM_2.5, although a fraction of secondary nitrate is also traffic-related but could not be estimated. Important contributions arise from secondary particles (nitrate, sulfate and organics) in PM_2.5 (37–82 %) but also in PM₁₀ (40–71 %), mostly at background sites, revealing the importance of abating gaseous precursors in designing air quality plans. Biomass burning (BB) contributions vary widely, from 14–24 % of PM₁₀ in POR-TR, MLN-UB and FI-UB, 7 % in ATH-SUB, to < 2 % in BCN-UB. In PM_2.5, BB is the second most important source in MLN-UB (21 %) and in POR-TR (18 %), the third one in FI-UB (21 %) and ATH-SUB (11 %), but is again negligible (< 2 %) in BCN-UB. This large variability among cities is mostly due to the degree of penetration of biomass for residential heating. In Barcelona natural gas is very well supplied across the city and is used as fuel in 96 % of homes, while in other cities, PM levels increase on an annual basis by 1–9 µg m⁻³ due to biomass burning influence. Other significant sources are the following. – Local dust, 7–12 % of PM₁₀ at SUB and UB sites and 19 % at the TR site, revealing a contribution from road dust resuspension. In PM_2.5 percentages decrease to 2–7 % at SUB-UB sites and 15 % at the TR site. – Industry, mainly metallurgy, contributing 4–11 % of PM₁₀ (5–12 % in PM_2.5), but only at BCN-UB, POR-TR and MLN-UB. No clear impact of industrial emissions was found in FI-UB and ATH-SUB. – Natural contributions from sea salt (13 % of PM₁₀ in POR-TR, but only 2–7 % in the other cities) and Saharan dust (14 % in ATH-SUB, but less than 4 % in the other cities). During high pollution days, the largest sources (i.e. excluding secondary aerosol factors) of PM₁₀ and PM_2.5 are VEX + NEX in BCN-UB (27–22 %) and POR-TR (31–33 %), BB in FI-UB (30–33 %) and MLN-UB (35–26 %) and Saharan dust in ATH-SUB (52–45 %). During those days, there are also quite important industrial contributions in BCN-UB (17–18 %) and local dust in POR-TR (28–20 %).

Organic aerosol (OA) is a key component of total submicron particulate matter (PM₁), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM₁ levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013-2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30-240 min) and long-term data coverage (9-36 months), providing essential information to improve/validate air quality, health impact, and climate models.

The 1st EuNetAir Air Quality Joint Intercomparison Exercise organized in Aveiro (Portugal) from 13th–27th October 2014, focused on the evaluation and assessment of environmental gas, particulate matter (PM) and meteorological microsensors, versus standard air quality reference methods through an experimental urban air quality monitoring campaign. The IDAD-Institute of Environment and Development Air Quality Mobile Laboratory was placed at an urban traffic location in the city centre of Aveiro to conduct continuous measurements with standard equipment and reference analysers for CO, NOx, O3, SO2, PM10, PM2.5, temperature, humidity, wind speed and direction, solar radiation and precipitation.The comparison of the sensor data generated by different microsensor-systems installed side-by-side with reference analysers, contributes to the assessment of the performance and the accuracy of microsensor-systems in a real-world context, and supports their calibration and further development.The overall performance of the sensors in terms of their statistical metrics and measurement profile indicates significant differences in the results depending on the platform and on the sensors considered. In terms of pollutants, some promising results were observed for O3 (r2: 0.12–0.77), CO (r2: 0.53–0.87), and NO2 (r2: 0.02–0.89). For PM (r2: 0.07–0.36) and SO2 (r2: 0.09–0.20) the results show a poor performance with low correlation coefficients between the reference and microsensor measurements. These field observations under specific environmental conditions suggest that the relevant microsensor platforms, if supported by the proper post processing and data modelling tools, have enormous potential for new strategies in air quality control

Levels of PM₁₀, PM_2.5 and PM₁ and chemical speciation of PM₁₀ and PM_2.5 were measured during the MILAGRO campaign (1st to 31st March 2006, but extended in some cases until 6th April) at four urban, one suburban, two rural background and two rural sites, with different degree of industrial influence, in the Mexico City Metropolitan Area (MCMA) and adjacent regions. PM₁₀ and PM_2.5 daily levels varied between 50–56μg/m³ and 24–46μg/m³ at the urban sites, 22–35μg/m³ and 13–25μg/m³ at the rural sites, and 75μg/m³ and 31μg/m³ at the industrial hotspot, lower than those recorded at some Asian mega-cities and similar to those recorded at other Latin American cities. At the urban sites, hourly PM_2.5 and PM₁ concentrations showed a marked impact of road traffic emissions (at rush hours), with levels of coarse PM remaining elevated during daytime. At the suburban and rural sites different PM daily patterns were registered according to the influence of the pollution plume from MCMA, and also of local soil resuspension. The speciation studies showed that mineral matter accounted for 25–27% of bulk PM₁₀ at the urban sites and a higher proportion (up to 43%) at the suburban and rural sites. This pattern is repeated in PM_2.5, with 15% at urban and 28% at suburban and rural sites. Carbonaceous compounds accounted for a significant proportion at the urban and industrial sites (32–46% in PM₁₀, and 51–55% in PM_2.5), markedly reduced at the suburban and rural sites (16–23% in PM₁₀, and 30% in PM_2.5). The secondary inorganic aerosols accounted for 10–20% of bulk PM₁₀ at urban, suburban, rural and industrial sites, with a higher proportion (40%) at the industrial background site. A relatively high proportion of nitrate in rural sites was present in the coarse fraction. Typically anthropogenic elements (As, Cr, Zn, Cu, Pb, Sn, Sb, Ba, among others) showed considerably high levels at the urban sites; however levels of particulate Hg and crustal trace elements (Rb, Ti, La, Sc, Ga) were generally higher at the suburban site. Principal component analysis identified three major common factors: crustal, regional background and road traffic. Moreover, some specific factors were obtained for each site.